Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
Sci2ools
International Keyboard
Graphical Social Symbols
CSS3 Style Generator
OCR
Web Page to Image
Web Page to PDF
Merge PDF
Split PDF
Latex Equation Editor
Extract Images from PDF
Convert JPEG to PS
Convert Latex to Word
Convert Word to PDF
Image Converter
PDF Converter
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
6
click to vote
EVOW
2006
Springer
favorite
Email
discuss
report
81
views
Artificial Intelligence
»
more
EVOW 2006
»
On the Use of Variable Complementarity for Feature Selection in Cancer Classification
13 years 8 months ago
Download
www.ulb.ac.be
Patrick Emmanuel Meyer, Gianluca Bontempi
Real-time Traffic
Artificial Intelligence
|
EVOW 2006
|
claim paper
Related Content
»
Feature selection and classification using flexible neural tree
»
Evolutionary selection of minimum number of features for classification of gene expression...
»
Gene selection from microarray data for cancer classification a machine learning approach
»
TwoPhase EAkNN for Feature Selection and Classification in Cancer Microarray Datasets
»
Machine Learning in DNA Microarray Analysis for Cancer Classification
»
Lymphoma Cancer Classification Using Genetic Programming with SNR Features
»
Classification of premalignant pancreatic cancer massspectrometry data using decision tree...
»
An Entropybased gene selection method for cancer classification using microarray data
»
Efficient hugescale feature selection with speciated genetic algorithm
more »
Post Info
More Details (n/a)
Added
22 Aug 2010
Updated
22 Aug 2010
Type
Conference
Year
2006
Where
EVOW
Authors
Patrick Emmanuel Meyer, Gianluca Bontempi
Comments
(0)
Researcher Info
Artificial Intelligence Study Group
Computer Vision